Target-enriched enzymatic methyl sequencing: flexible, scalable and inexpensive hybridization capture for quantifying DNA methylation

Abstract

The increasing interest in studying DNA methylation to understand how traits or diseases develop requires new and flexible approaches for quantifying DNA methylation in a diversity of organisms. In particular, we need efficient yet cost-effective ways to measure CpG methylation states over large and complete regions of the genome. Here, we develop TEEM-Seq (target-enriched enzymatic methyl sequencing), a method that combines enzymatic methyl sequencing with a custom-designed hybridization capture bait set that can be scaled to reactions including large numbers of samples in any species for which a reference genome is available. Using DNA from a passerine bird, the superb starling (Lamprotornis superbus), we show that TEEM-Seq is able to quantify DNA methylation states similarly well to the more traditional approaches of whole-genome and reduced-representation sequencing. Moreover, we demonstrate its reliability and repeatability, as duplicate libraries from the same samples were highly correlated. Importantly, the downstream bioinformatic analysis for TEEM-Seq is the same as for any sequence-based approach to studying DNA methylation, making it simple to incorporate into a variety of workflows. We believe that TEEM-Seq could replace traditional approaches for studying DNA methylation in candidate genes and pathways, and be effectively paired with other whole-genome or reduced-representation sequencing approaches to increase project sample sizes. In addition, TEEM-Seq can be combined with mRNA sequencing to examine how DNA methylation in promoters or other regulatory regions is related to the expression of individual genes or gene networks. By maximizing the number of samples in the hybridization reaction, TEEM-Seq is an inexpensive and flexible sequence-based approach for quantifying DNA methylation in species where other capture-based methods are unavailable or too expensive, particularly for non-model organisms.